copula: qqplot2 – R documentation

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qqplot2

Q-Q Plot with Rugs and Pointwise Asymptotic Confidence Intervals

Description

A Q-Q plot (possibly) with rugs and pointwise approximate (via the Central Limit Theorem) two-sided 1-alpha confidence intervals.

Usage

qqplot2(x, qF, log = "", qqline.args = if(log=="x" || log=="y")
        list(untf=TRUE) else list(),
        rug.args = list(tcl=-0.6*par("tcl")),
        alpha = 0.05, CI.args = list(col="gray40"),
        CI.mtext = list(text=paste0("Pointwise asymptotic ", 100*(1-alpha),
                        "% confidence intervals"), side=4,
                        cex=0.6*par("cex.main"), adj=0, col="gray40"),
        main = quote(bold(italic(F)~~"Q-Q plot")),
        main.args = list(text=main, side=3, line=1.1, cex=par("cex.main"),
                         font=par("font.main"), adj=par("adj"), xpd=NA),
        xlab = "Theoretical quantiles", ylab = "Sample quantiles",
        file="", width=6, height=6, ...)

Arguments

`x`	`numeric`.
`qF`	(theoretical) quantile function against which the Q-Q plot is created.
`log`	`character` string indicating whether log-scale should be used; see `?plot.default`.
`qqline.args`	argument `list` passed to `qqline()` for creating the Q-Q line. Use `qqline.args=NULL` to omit the Q-Q line.
`rug.args`	argument `list` passed to `rug()` for creating the rugs. Use `rug.args=NULL` to omit the rugs.
`alpha`	significance level.
`CI.args`	argument `list` passed to `lines()` for plotting the confidence intervals. Use `CI.args=NULL` to omit the confidence intervals.
`CI.mtext`	argument `list` passed to `mtext()` for plotting information about the confidence intervals. Use `CI.mtext=NULL` to omit the information.
`main`	title (can be an expression; use "" for no title).
`main.args`	argument `list` passed to `mtext()` for plotting the title. Use `main.args=NULL` to omit the title.
`xlab`	x axis label.
`ylab`	y axis label.
`file`	file name including the extension “.pdf”.
`width`	width parameter of `pdf()`.
`height`	height parameter of `pdf()`.
`...`	additional arguments passed to `plot()` based for plotting the points.

Details

See the source code for how the confidence intervals are constructed precisely.

Value

invisible().

Examples

n <- 250
df <- 7
set.seed(1)
x <- rchisq(n, df=df)

## Q-Q plot against the true quantiles (of a chi^2_3 distribution)
qqplot2(x, qF = function(p) qchisq(p, df=df),
        main = substitute(bold(italic(chi[NU])~~"Q-Q Plot"), list(NU=df)))

## in log-log scale
qqplot2(x, qF = function(p) qchisq(p, df=df), log="xy",
        main = substitute(bold(italic(chi[NU])~~"Q-Q Plot"), list(NU=df)))

## Q-Q plot against wrong quantiles (of an Exp(1) distribution)
qqplot2(x, qF=qexp, main = quote(bold(Exp(1)~~"Q-Q Plot")))

copula

Multivariate Dependence with Copulas

v1.0-1

GPL (>= 3) | file LICENCE

Authors

Marius Hofert [aut] (<https://orcid.org/0000-0001-8009-4665>), Ivan Kojadinovic [aut] (<https://orcid.org/0000-0002-2903-1543>), Martin Maechler [aut, cre] (<https://orcid.org/0000-0002-8685-9910>), Jun Yan [aut] (<https://orcid.org/0000-0003-4401-7296>), Johanna G. Nešlehová [ctb] (evTestK(), <https://orcid.org/0000-0001-9634-4796>), Rebecca Morger [ctb] (fitCopula.ml(): code for free mixCopula weight parameters)

Initial release

2020-12-07